susan.m

susan 算法的实现

function image_out = susan(im,threshold)
close all
clc
% check to see if the image is a color image...
d = length(size(im));
if d==3
    image=double(rgb2gray(im));
elseif d==2
    image=double(im);
end
% mask for selecting the pixels within the circular region (37 pixels, as
% used in the SUSAN algorithm
mask = ([ 0 0 1 1 1 0 0 ;0 1 1 1 1 1 0;1 1 1 1 1 1 1;1 1 1 1 1 1 1;1 1 1 1 1 1 1;0 1 1 1 1 1 0;0 0 1 1 1 0 0]);
% the output image indicating found edges
R=zeros(size(image));
% define the USAN area
nmax = 3*37/4;
% padding the image
[a b]=size(image);
new=zeros(a+7,b+7);
[c d]=size(new);
new(4:c-4,4:d-4)=image;
for i=4:c-4 
   for j=4:d-4   
        current_image = new(i-3:i+3,j-3:j+3);
        current_masked_image = mask.*current_image;
%   Uncomment here to implement binary thresholding
%         current_masked_image(find(abs(current_masked_image-current_masked_image(4,4))>threshold))=0;         
%         current_masked_image(find(abs(current_masked_image-current_masked_image(4,4))<=threshold))=1;
%   This thresholding is more stable              
       current_thresholded = susan_threshold(current_masked_image,threshold);
        g=sum(current_thresholded(:)); 
        if nmax<g
            R(i,j) = g-nmax;
        else
            R(i,j) = 0;
        end
    end
end
image_out=R(4:c-4,4:d-4);